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The first vaccines for prevention of coronavirus disease 2019 (COVID-19) in the United States were authorized for emergency use by the Food and Drug Administration (FDA) (1) and recommended by the Advisory Committee on Immunization Practices (ACIP) in December 2020.* However, demand for COVID-19 vaccines is expected to exceed supply during the first months of the national COVID-19 vaccination program. ACIP advises CDC on population groups and circumstances for vaccine use.† On December 1, ACIP recommended that 1) health care personnel§ and 2) residents of long-term care facilities¶ be offered COVID-19 vaccination first, in Phase 1a of the vaccination program (2). On December 20, 2020, ACIP recommended that in Phase 1b, vaccine should be offered to persons aged ≥75 years and frontline essential workers (non-health care workers), and that in Phase 1c, persons aged 65-74 years, persons aged 16-64 years with high-risk medical conditions, and essential workers not recommended for vaccination in Phase 1b should be offered vaccine.** These recommendations for phased allocation provide guidance for federal, state, and local jurisdictions while vaccine supply is limited. In its deliberations, ACIP considered scientific evidence regarding COVID-19 epidemiology, ethical principles, and vaccination program implementation considerations. ACIP’s recommendations for COVID-19 vaccine allocation are interim and might be updated based on changes in conditions of FDA Emergency Use Authorization, FDA authorization for new COVID-19 vaccines, changes in vaccine supply, or changes in COVID-19 epidemiology.


Ubiquitous facial recognition technology can expose individuals' political orientation, as faces of liberals and conservatives consistently differ. A facial recognition algorithm was applied to naturalistic images of 1,085,795 individuals to predict their political orientation by comparing their similarity to faces of liberal and conservative others. Political orientation was correctly classified in 72% of liberal-conservative face pairs, remarkably better than chance (50%), human accuracy (55%), or one afforded by a 100-item personality questionnaire (66%). Accuracy was similar across countries (the U.S., Canada, and the UK), environments (Facebook and dating websites), and when comparing faces across samples. Accuracy remained high (69%) even when controlling for age, gender, and ethnicity. Given the widespread use of facial recognition, our findings have critical implications for the protection of privacy and civil liberties.


Dogs (Canis familiaris) are the first animals to be domesticated by humans and the only ones domesticated by mobile hunter-gatherers. Wolves and humans were both persistent, pack hunters of large prey. They were species competing over resources in partially overlapping ecological niches and capable of killing each other. How could humans possibly have domesticated a competitive species? Here we present a new hypothesis based on food/resource partitioning between humans and incipient domesticated wolves/dogs. Humans are not fully adapted to a carnivorous diet; human consumption of meat is limited by the liver’s capacity to metabolize protein. Contrary to humans, wolves can thrive on lean meat for months. We present here data showing that all the Pleistocene archeological sites with dog or incipient dog remains are from areas that were analogous to subarctic and arctic environments. Our calculations show that during harsh winters, when game is lean and devoid of fat, Late Pleistocene hunters-gatherers in Eurasia would have a surplus of animal derived protein that could have been shared with incipient dogs. Our partitioning theory explains how competition may have been ameliorated during the initial phase of dog domestication. Following this initial period, incipient dogs would have become docile, being utilized in a multitude of ways such as hunting companions, beasts of burden and guards as well as going through many similar evolutionary changes as humans.


The most restrictive non-pharmaceutical interventions (NPIs) for controlling the spread of COVID-19 are mandatory stay-at-home and business closures. Given the consequences of these policies, it is important to assess their effects. We evaluate the effects on epidemic case growth of more restrictive NPIs (mrNPIs), above and beyond those of less restrictive NPIs (lrNPIs).


The association of air pollution with multiple adverse health outcomes is becoming well established, but its negative economic impact is less well appreciated. It is important to elucidate this impact for the states of India.


The ability to control autoreactive T cells without inducing systemic immune suppression is the major goal for treatment of autoimmune diseases. The key challenge is the safe and efficient delivery of pharmaceutically well-defined antigens in a noninflammatory context. Here, we show that systemic delivery of nanoparticle-formulated 1 methylpseudouridine-modified messenger RNA (m1Ψ mRNA) coding for disease-related autoantigens results in antigen presentation on splenic CD11c+ antigen-presenting cells in the absence of costimulatory signals. In several mouse models of multiple sclerosis, the disease is suppressed by treatment with such m1Ψ mRNA. The treatment effect is associated with a reduction of effector T cells and the development of regulatory T cell (Treg cell) populations. Notably, these Treg cells execute strong bystander immunosuppression and thus improve disease induced by cognate and noncognate autoantigens.


Estimates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease burden are needed to help guide interventions.


During early August 2020, county-level incidence of coronavirus disease 2019 (COVID-19) generally decreased across the United States, compared with incidence earlier in the summer (1); however, among young adults aged 18-22 years, incidence increased (2). Increases in incidence among adults aged ≥60 years, who might be more susceptible to severe COVID-19-related illness, have followed increases in younger adults (aged 20-39 years) by an average of 8.7 days (3). Institutions of higher education (colleges and universities) have been identified as settings where incidence among young adults increased during August (4,5). Understanding the extent to which these settings have affected county-level COVID-19 incidence can inform ongoing college and university operations and future planning. To evaluate the effect of large colleges or universities and school instructional format* (remote or in-person) on COVID-19 incidence, start dates and instructional formats for the fall 2020 semester were identified for all not-for-profit large U.S. colleges and universities (≥20,000 total enrolled students). Among counties with large colleges and universities (university counties) included in the analysis, remote-instruction university counties (22) experienced a 17.9% decline in mean COVID-19 incidence during the 21 days before through 21 days after the start of classes (from 17.9 to 14.7 cases per 100,000), and in-person instruction university counties (79) experienced a 56.2% increase in COVID-19 incidence, from 15.3 to 23.9 cases per 100,000. Counties without large colleges and universities (nonuniversity counties) (3,009) experienced a 5.9% decline in COVID-19 incidence, from 15.3 to 14.4 cases per 100,000. Similar findings were observed for percentage of positive test results and hotspot status (i.e., increasing among in-person-instruction university counties). In-person instruction at colleges and universities was associated with increased county-level COVID-19 incidence and percentage test positivity. Implementation of increased mitigation efforts at colleges and universities could minimize on-campus COVID-19 transmission.


The coronavirus (COVID-19) pandemic and attendant lockdown measures present serious threats to emotional well-being worldwide. Here, we examined the extent to which being outdoors (vs. indoors), the experience of loneliness, and screen-time are associated with emotional well-being during the COVID-19 pandemic using an experiencing sampling method. In April 2020, Austrian adults (N = 286, age M = 31.0 years) completed a 21-day experience sampling phase in which they reported their emotional well-being (i.e., happiness), whether they were indoors or outdoors, and loneliness at three random time-points each day, as well as their daily screen-time. Results indicated that being outdoors was associated with higher emotional well-being, whereas greater loneliness and greater daily screen-time were associated with poorer well-being. Additionally, the impact of loneliness on well-being was weaker when participants were outdoors than indoors. These results have health policy implications for the promotion of population well-being during pandemics.


Nasopharyngeal swabs are the primary sampling method used for detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but they require a trained health care professional and extensive personal protective equipment.